In this session, we’ll walk through the architectural, operational, and governance decisions that define enterprise-ready GenAI systems, including: Key takeaways: → Designing for real-time performance, throughput, and latency across use cases. → Choosing between proprietary models, open source, and fine-tuned LLMs and managing that complexity over time. → Building observability and feedback loops into your stack to track model drift and measure business impact. → Putting the right controls in place for data privacy, access, and regulatory compliance.